The objective of this work was to develop a computational model for better understanding of the process of producing contrast agent, used in Magnetic Resonance Imaging (MRI). Contrast agents are used to provide high-resolution anatomical and functional information to identify tumor growth for prostrate and breast cancers. The production process for the contrast agents involves melting and dissolution of the imaging agent (maintained at very low temperature ∼1K to retain its polarization capability) by injecting the jet of alkaline solvent. Dissolution should happen in minimum time to allow for time required to inject contrast agent into the patient with sufficient time to travel to the targeted organ. This process involves multi-phase, multi-species and chemically reacting fluid dynamics. The intricacy and complexity of the melting process and very small time scales (order of a few milliseconds) poses practical challenges of collecting enough experimental data for the better understanding of such processes. It creates a need for looking at these kinds of processes from a numerical point of view. A computational model was developed in commercial software to capture the relevant physics involved in the flow-thermal process. System was analyzed to guide design changes with the objective of minimizing the melting time of imaging agent. Model predictions were validated against experiments and sensitivity studies were carried out pertaining to operating parameters such as solvent flow rate, temperature and other geometrical parameters. The predictions from model gave an insight into the process. It was found that melting time is not only a function of operating conditions and geometrical parameters but also a function of nature of the multiphase flow. Other than solid and molten phase, vapor phase (vaporization of the alkaline solvent) also coexist in the system under certain operating conditions; which further complicates the process. Desired operating conditions and geometrical changes were recommended to minimize the melting time. It is believed that current findings and numerical modeling approach could be utilized in other similar processes.

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